Several warm winter events have occurred across the Southeast in the past decade, including 2 major events in 2017 and 2018 in Georgia and South Carolina. Plants will begin their spring growth sooner than climatology would suggest and then be damaged by early spring frosts in what is commonly known as a "false spring" event. Some species of plants, like peaches and blueberries, which produce buds early in the season, are just an example of some of the agricultural products more at risk than others. As an important measure of dormancy time in plants, chill hours present a measurement capable of tracking phenological shifts in plants. While a lack of required chill hours can delay spring emergence, intense warm periods can override the chilling hour requirement and induce spring emergence. This project involves training self-organizing maps (SOMs) to identify periods of anomalous winter warming based on a reduced number of chill hours within a 5-day temporal period compared to the period's climatological average. A second SOM is nested in the node that produced the most anomalous events to identify the range of warming that occurs in the most anomalous events, the synoptic setups of these events, and when these occurred. Hourly 2-meter temperature from ERA5 is used to conduct this analysis over a domain centered primarily over South Carolina and Georgia with a temporal period of 1980-2020. Climatological examination of chill hour accumulations in the past 4 decades show an overall decrease in chill hour accumulation across the past decade (2011-2020) Results indicated that periods of higher-than-average temperatures are increasing with time while periods of average or lower than average temperatures are decreasing with time. Both results were statistically significant by Mann-Kendall test. The results of the nested SOMs suggest that an increase in patterns of southerly flow (a common pattern for warmer temperatures) is occurring through time. A third SOM investigating early spring hard freezes was inconclusive but illustrated that some years had more early spring frosts than others independent of how many warmer than average periods occurred in the main winter. The use of SOMs for investigating climatological and synoptic changes in winter and early spring proved successful and effective. Future modifications to these SOMs could be used to identify more trends that exist within these seasons. / Master of Science / Several warm winter events have occurred across the Southeast in the past decade, including 2 major events in 2017 and 2018 in Georgia and South Carolina. Plants will begin their spring growth sooner than climatology would suggest and then be damaged by early spring frosts in what is commonly known as a "false spring" event. Some species of plants, like peaches and blueberries, which produce buds early in the season, are just an example of some of the agricultural products more at risk than others. As an important measure of dormancy time in plants, chill hours present a measurement capable of tracking shifts from normal winter to spring transition in plants. While a lack of required chill hours can delay leaf emergence and spring blooms, intense warm periods can override the chilling hour requirement and induce this spring emergence. This project involves training self-organizing maps (SOMs), a machine learning model, to identify periods of anomalous winter warming based on a reduced number of chill hours within a 5-day temporal period compared to the period's climatological average. A second SOM is nested in the node that produced the most anomalously warm events to identify the range of warming that occurs in the most anomalous events, the large-scale meteorological setups of these events, and when these occurred. Hourly 2-meter temperature from ERA5, a climatological dataset, is used to conduct this analysis over a domain centered primarily over South Carolina and Georgia with a temporal period of 1980-2020. Climatological examination of chill hour accumulations in the past 4 decades show an overall decrease in chill hour accumulation across the past decade (2011-2020) Results indicated that periods of higher-than-average temperatures are increasing with time while periods of average or lower than average temperatures are decreasing with time. Both of these trend findings were statistically significant by Mann-Kendall test. The results of the nested SOMs suggest that an increase in patterns of southerly flow (a common pattern for warmer temperatures) is occurring through time. A third SOM investigating early spring hard freezes (temperatures low enough to cause damage to plant cellular structures) was inconclusive but illustrated that some years had more early spring frosts than others independent of how many warmer than average periods occurred in the main winter. The use of SOMs for investigating climatological and synoptic changes in winter and early spring proved successful and effective. Future modifications to these SOMs could be used to identify more trends that exist within these seasons.